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Computational Chemistry
There are several ongoing projects on accelerating quantum chemistry codes using CUDA-enabled GPUs, including work on Gaussian and GAMESS. The charts below are representative results, followed by links to software and technical reports on CUDA acceleration of computational chemistry.
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| Direct self-consistent field (SCF) calculations Ufimtsev and Martinez |
Two-Electron integral evaluation Koji Yasuda |
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- Learn about GPU acceleration in VMD
- NAMD 2.7 Beta 2 including CUDA Acceleration
- HOOMD: Highly Optimized Object Oriented Molecular Dynamics
- OpenMM library for Accelerating Molecular Dynamics on GPUs
- GROMACS using OpenMM
- AMBER CUDA Port
- LAMMPS GPU Port
- TeraChem: First Quantum Chemistry Code Written Ground-up for CUDA GPUs
- ACE-MD
- MDGPU
- GPUGrid.net
- BigDFT : DFT (Density Functional Theory) Electronic Structure Code -- Paper PDF
- PC GAMESS on CUDA
- Todd Martinez work on Quantum Chemistry on GPUs
- Q-Chem on CUDA
- An implementation of the Smooth Particle-Mesh Ewald (PME) Method on GPU Hardware
- Two-Electron Integral Evaluation on the GPU
- Acceleration of Fragment MO (FMO) Method using CUDA
- NAMD and VMD Publications
- Molecular Dynamics on a GPU Grid
GPU Technology Conference 2012
- Enabling Faster Material Science Modeling Using the Accelerated Quantum Espresso – Irish Centre for High-End Computing
- A Quantum Chemistry Domain-Specific Language for Heterogeneous Clusters– Pacific Northwest National Labs
- VASP Accelerated with GPUs– University of Chicago
- Large-Scale First Principle Pseudopotential DFT Calculations on GPU Cluster– Chinese Academy of Sciences
- Quantum Chemistry: Automated Code Generation and Optimization for GPU Kernels – Stanford
More presentations are available on GTC On-Demand.
SC09 Presentations- Overview of NVIDIA CUDA Support in AMBER - Lessons Learned, Capabilities Gained, Ross Walker, University of California San Diego, San Diego Supercomputing Center
- Harnessing GPU Speed to Accelerate LAMMPS Particle Simulation, Paul Crozier, Sandia National Laboratory
- Accelerating Molecular Modeling Applications with GPU Computing, John Stone, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign